Sökning: "reward systems"
Visar resultat 1 - 5 av 73 avhandlingar innehållade orden reward systems.
1. Safe, human-like, decision-making for autonomous driving
Sammanfattning : Autonomous driving technology can significantly improve transportation by saving lives and social costs and increasing traffic efficiency and availability. Decision-making is a critical component of driving ability. Complex traffic environments and interactions between road users bring about many challenges in decision-making. LÄS MER
2. Reward-related genes and alcohol dependence
Sammanfattning : Introduction: The rewarding properties of alcohol are mediated by the brain reward systems, specifically by the cholinergic-dopaminergic reward link, involving both nicotinic acetylcholine receptors (nAChRs) as well as the ghrelin signalling system. The susceptibility for developing alcohol dependence is influenced by genetic factors. LÄS MER
3. Games and Probabilistic Infinite-State Systems
Sammanfattning : Computer programs keep finding their ways into new safety-critical applications, while at the same time growing more complex. This calls for new and better methods to verify the correctness of software. We focus on one approach to verifying systems, namely that of model checking. LÄS MER
4. Designing Trustworthy Autonomous Systems
Sammanfattning : The design of autonomous systems is challenging and ensuring their trustworthiness can have different meanings, such as i) ensuring consistency and completeness of the requirements by a correct elicitation and formalization process; ii) ensuring that requirements are correctly mapped to system implementations so that any system behaviors never violate its requirements; iii) maximizing the reuse of available components and subsystems in order to cope with the design complexity; and iv) ensuring correct coordination of the system with its environment. Several techniques have been proposed over the years to cope with specific problems. LÄS MER
5. Reinforcement Learning and Dynamical Systems
Sammanfattning : This thesis concerns reinforcement learning and dynamical systems in finite discrete problem domains. Artificial intelligence studies through reinforcement learning involves developing models and algorithms for scenarios when there is an agent that is interacting with an environment. LÄS MER